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AI3SD Video: The Shape of Data in Chemistry – Insights Gleaned from Complex Solutions and Their Interfaces

AI3SD Video: The Shape of Data in Chemistry – Insights Gleaned from Complex Solutions and Their Interfaces
AI3SD Video: The Shape of Data in Chemistry – Insights Gleaned from Complex Solutions and Their Interfaces
Highly non-ideal solutions are ever-present within chemistry, physics, and materials science – and are characterized by many-body effects across length and timescale. Understanding, and predicting, many-body correlations in the condensed phase is a grand challenge for the modeling and simulation community. Yet within the data science community, a large suite of tools exist for elucidating complex, correlating, relationships amongst variables. Molecular modeling and simulation data is in fact well-suited for study by methods that include the topology of graphs, point cloud data, and recent advances in applied mathematics methods that investigate surfaces like sublevel set persistent homology and geometric measure theory. We adapt, develop, and apply these tools to study highly non-ideal solutions and their interfaces, with examples drawn from separations science. The new physical insight derived from these methods is paving the way for bespoke liquid/liquid interfaces that optimize transport characteristics for purification and synthesis.
AI3SD Event, Chemistry, Geometry, Mathematics, Molecules, Topological Data Analysis, Topology
Clark, Aurora
1c1a110f-749c-457c-b8fe-9ffad548a31d
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Clark, Aurora
1c1a110f-749c-457c-b8fe-9ffad548a31d
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Clark, Aurora (2020) AI3SD Video: The Shape of Data in Chemistry – Insights Gleaned from Complex Solutions and Their Interfaces. Kanza, Samantha, Frey, Jeremy G., Niranjan, Mahesan and Hooper, Victoria (eds.) AI3SD Winter Seminar Series, , Online. 18 Nov 2020 - 21 Apr 2021 . (doi:10.5258/SOTON/P0087).

Record type: Conference or Workshop Item (Other)

Abstract

Highly non-ideal solutions are ever-present within chemistry, physics, and materials science – and are characterized by many-body effects across length and timescale. Understanding, and predicting, many-body correlations in the condensed phase is a grand challenge for the modeling and simulation community. Yet within the data science community, a large suite of tools exist for elucidating complex, correlating, relationships amongst variables. Molecular modeling and simulation data is in fact well-suited for study by methods that include the topology of graphs, point cloud data, and recent advances in applied mathematics methods that investigate surfaces like sublevel set persistent homology and geometric measure theory. We adapt, develop, and apply these tools to study highly non-ideal solutions and their interfaces, with examples drawn from separations science. The new physical insight derived from these methods is paving the way for bespoke liquid/liquid interfaces that optimize transport characteristics for purification and synthesis.

Video
AI3SDWinterSeminarSeries-1-Topology-AC-181120 - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 18 November 2020
Additional Information: Aurora Clark is a Professor of Chemistry at Washington State University. Her research employs both quantum and statistical mechanics to study chemical processes within complex chemical environments, focusing upon solution chemistry and liquid interfaces. This includes concentrated electrolytes, liquid/liquid interfaces related to separations science, structured fluids, and phase phenomena. To reveal the hierarchical organization and dynamic behavior in such systems, her laboratory has expanded the tools of graph theory, algebraic and geometric topology, to analyze data from modeling and simulation. Of particular interest is bridging the separate communities of applied mathematics with Chemistry and Materials Science by creating algorithms that are well-suited to simulation data and that provide new physical insight. Dr. Clark is the author of more than 100 publications and is a Fellow of the American Chemical Society and the American Association for the Advancement of Science.
Venue - Dates: AI3SD Winter Seminar Series, , Online, 2020-11-18 - 2021-04-21
Keywords: AI3SD Event, Chemistry, Geometry, Mathematics, Molecules, Topological Data Analysis, Topology

Identifiers

Local EPrints ID: 448783
URI: http://eprints.soton.ac.uk/id/eprint/448783
PURE UUID: c0188bd8-7c36-43ac-a4d3-84fa391cc7bc
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302

Catalogue record

Date deposited: 05 May 2021 16:53
Last modified: 06 May 2021 01:59

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Contributors

Author: Aurora Clark
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Mahesan Niranjan
Editor: Victoria Hooper

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